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DTSTART;VALUE=DATE:20260528
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DTSTAMP:20260622T175746
CREATED:20260612T204356Z
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SUMMARY:Visit from Vilnius University
DESCRIPTION:Prof. Daumantas Matulis and Dr. Vytautas Petrauskas as a part of ongoing collaborative discussions that began with the visit of the Lithuanian delegation to York. \nProf. Daumantas Matulis and Dr. Vytautas Petrauskas are from the Department of Biothermodynamics and Drug Design\, Life Sciences Center\, Vilnius University. Their research interests are closely related to biomolecular interactions\, biophysical analysis\, and drug discovery\, so I expect the presentation and discussion to be scientifically engaging. \n— \nDrug Design and Protein–Ligand Binding Database for AI-ML\nProf. Daumantas Matulis\nHead of Department of Biothermodynamics and Drug Design\, Institute of Biotechnology\, Vilnius\nUniversity\, Saulėtekio 7\, Vilnius LT-10257\, Lithuania Email: daumantas.matulis@bti.vu.lt\,\nmatulis@ibt.lt \nAbstract\nDrug molecules exert their effects on disease-associated proteins by binding to them with high\naffinity and selectivity. However\, most small molecules interact only weakly with the majority of\nsites on protein surfaces\, and only a limited number of chemical compounds can selectively and\nstrongly bind to desired sites. In addition\, even minor modifications to a compound’s chemical\nstructure may lead to substantial changes in binding affinity. We designed and investigated the\nbinding of over 1\,000 small-molecule compounds to Carbonic Anhydrase IX\, a transmembrane\nprotein overexpressed in hypoxic solid tumors that promotes metastasis and invasiveness\, and\nsupports cancer cell survival under hypoxic conditions by acidifying the tumor microenvironment.\nWe characterized the thermodynamics of binding of these compounds across the carbonic\nanhydrase enzyme family and identified the determinants of selectivity for CA IX inhibition (1) .\nFluorescent CA IX-selective compounds enabled visualization of CA IX expression in cancer cells\nand tumors and demonstrated efficacy against Neuroblastoma in mouse xenograft models.\nThe data were assembled into the Protein-Ligand Binding Database (PLBD) to apply artificial\nintelligence – machine learning approaches to drug design and are available at https://plbd.org\n(2) . The database contains 8233 binding datasets of 792 compounds interacting with human CA\nisozymes\, Hsp90\, and COVID proteases\, as determined by inhibition of enzymatic activity\, TSA\, ITC\,\nand SPR techniques. The PLBD emphasizes intrinsic parameters and enthalpy\, enhancing the\nunderstanding of reaction mechanisms. The binding data are linked to 138 crystal structures of CA\ncomplexes with ligands. The database has been built using the FAIR data principles to contain the\nraw data with revision and versioning systems. The PLBD led to a deeper understanding of the\nprotein-ligand recognition principles and enabled the achievement of femtomolar affinities in\nsmall-molecule drug design (3) . \nReferences\n1. Matulis\, D. 2019. Carbonic anhydrase as drug target: thermodynamics and structure of inhibitor\nbinding. SPRINGER NATURE.\n2. Lingė\, D.\, M. Gedgaudas\, A. Merkys\, V. Petrauskas\, A. Vaitkus\, A. Grybauskas\, V. Paketurytė\, A.\nZubrienė\, A. Zakšauskas\, A. Mickevičiūtė\, J. Smirnovienė\, L. Baranauskienė\, E. Čapkauskaitė\, V.\nDudutienė\, E. Urniežius\, A. Konovalovas\, E. Kazlauskas\, K. Shubin\, H.B. Schiöth\, W.-Y. Chen\, J.E.\nLadbury\, S. Gražulis\, and D. Matulis. 2023. PLBD: protein–ligand binding database of thermodynamic\nand kinetic intrinsic parameters. Database 2023:baad040\, doi: 10.1093/database/baad040.\n3. Zubrienė\, A.\, M. Kurtenoka\, V. Paketurytė-Latvė\, J. Leitans\, E. Manakova\, M. Žvirblis\, A. Kazaks\, V.\nEimonta\, K. Tars\, S. Gražulis\, V. Petrauskas\, J. Matulienė\, V. Dudutienė\, K. Shubin\, and D. Matulis. 2026.\nAchieving femtomolar affinities in structure-based drug design. Eur. Biophys. J.\, doi: 10.1007/s00249-\n025-01812-5. \n\n 
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CATEGORIES:Seminars
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